{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3, 6, 1, 9, 5]\n",
      "[1, 2, 3, 4, 5, 6, 7, 8, 9]\n"
     ]
    }
   ],
   "source": [
    "# 从数组中获取样本\n",
    "\n",
    "import random\n",
    "y=list(range(1,10))\n",
    "slice = random.sample(y, 5)  #从list中随机获取5个元素，作为一个片断返回  \n",
    "print (slice)  \n",
    "print (y) #原有序列并没有改变。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bNTQDA2UFZSdg5JV5VhPfOXkT+3/1r33BkjFvQsL5CMP0XBMAx9x1f0JVloiv+IghTUKVnUe/Wya6vwzbb2ZBjGLjLT2oucuFymltw4JF7Yfb9rF0gZB1hNw6anfUjLuW3r0wi7fOTufc22TwiteIe0zXF9aOuR+bWsCjO0exw9mX1dTdey+4RzQFMy3Lz9zldI2fuhl8gIkLNoZpYSFiQIlmWNBN6jJ3oLfa/p69tYyltoFbnM+byTJDZSWUgzFMC4R47ipRQrWhmRhQZRBCEAQL+EmYMmvlIGbuouBuvzYxVA7tE4Nu2t+XL7grxVYWsxUDS6gCyYM76wi5ZcQO7nHtLP7NX3+EX//Oh3l2NTFMR54lxJZlAGBqbnX95Qw3F1u4sdjCIzvHsGODE9znV29fejC4RzP3cEK1d4JXHPiAHseQdJNivinW9HjbHwt07R5yzDCmyD+8GAMeraphn7tF3WI2IDqhKpJkAFvWA5KtbljADWrugFiWCTJ3kSzTEkhGFVUutCcQ3zjNZZYJk6rMKbOVBfeYh2BTN1dNl9c5kjdQUnD/lmG89uHtVfnsII46Yz4f3TWK0aqK4bLSZ+5xUCL6xpiWX3O3rZDrg7nzASZOljEsCy3dEi7zWUAZLMtecO+iRFgnzDsFM3xwZ0FxuKIKmTv/sI+qUBUlUwGgzJrPJWHuznv8vWXs4C6yQ7IH7fhQdEKVrarKAeaumdHWybRg10S1JGPTUBmqTBIzd+Zxd2WZmPPU1sWJ5ZVAMPf2o4/twKFLc7Fy5Urh2NQCZIlg7zZ7Bu6ODdW+5h4H2WXu4XJzOSTL9E7wioNueDdznNTEVjOLAmmGZ+6eLNNDzN05pkUBcx+uKIIKVf9N7laocsy3ofkTljxKmZg7b4WMTqiyRPB4jObOD+oIHkNRgZL/DEki2DpaSR7cGzpKsoQxx/ETJxe1DHPV7kV7Be+FtR/5xHYAwNfXYIj30al53L9l2F197dxQXdUq1UTBnRDyGULIh4SQs4SQXxT8fjch5DVCyGFCyDFCyA8Vv6s2oouYLFePB9anzx3owNydACfS3VlAsX3u4UDX7VgQMPe6ZqAkS6iocqga2bAs303OEqf+IiYjkrmnccu0hJp754TqeIzm3hQE96Ifyp4V1N7X7aPJ7ZBzdQ1jAyoqSufcxGoydyOQe9s+VsUzd23Efzl8dVXdYZRSO5m6a9R9bcdYlzF3QogM4DcAfBbAXgBfIITsDbztlwB8jVL6GIDPA/jNoneUwWs/IGgc5pNl1hFzT5FQBTyWy6Pu09zZDdlLzN3R3Bt+WaZakqEKqpGNAHMH2ASqoCwTbj0ApHPLsMDGB3dvYEeMLOMy9/BnuMnOkrfNouU0zwpqf8aOFIVMcw0NGwdL7nmKDe6GtWrOrGAcAIAfe2wHLkzX3TYAq4FLMw0sNHU8snPMfW3HhiqWWkak6aFoJGHuTwE4Syk9TynVAPwJgB8JvIcCYCPkRwFcK24X/VATNA6z37dONfe4hKpzTvgAyNBoe5o7s+z1EnMXae5MM1cE37VuUvdaYaiW/AM7YhOqKdwymhvcvW0psoSBkiz0jXvMPTqh6o1E9DcOA4pj7mzUX1V1mPtYFTcWW4k863MNm7mzY44jCu3VTKgKvvfPPrwNJUXC1w+vnjTz/uU5AMAndnHBfcxpQ7xK0kyS4L4DwBXu31POazz+TwA/QQiZAvBNAP+kkL0TIEpzNwNumdXU3M/eWsZfHVu5Xs38kjZellmfzJ1Sr9Q9mFAdKMlQJCmcgwm0owC8gR0MsQnVFBWqIrcMwJqHRec/xgc7yzIVnywT7myZB8Eiru1jVZgW9dlNozDX0LFxsOQec2xC1bBW7V4UMfeRiooffHAL/uLotVXbj/cuzmG4Yrt1GDw75OoEd/Ga1I+wCdhm6jy+AOD3KaX/NyHkWQB/SAjZRyn1nUlCyBcBfBEAtmzZgsnJydQ7fKthb/L4iZMYnT/jvr641MAsGu42FxdaaOg002ekxVdPtfHaFQMDMwNCz3ReXL/pLZUPvn8ErcvigNTS7EBy6INTmFg66/vd4Sv27469/y4YsT909APIN08Vvr9FYXl5GZOTk2ib1A0e565cx+SkzYqu3GjBbFPMTLewVLd83/X1Gy1oLf9rptbC1PWb7msL9SbmpzXhNTLXsj/vxKnT2LR8LnY/D920g/UHR97H4nnvu5FNDee5/WU4ccaWmA6/+yYIgNNnz2OSTPmO+dANe5snjh7G4nk7gJ65Zb/21jvv4cao+BpIgyOX7QvhyMF3cKkiYfq2vf2/eu0t3Lshfvs35+vYWW7hgyO23e/QkWPA9XA4sSiFZlogJiLvRXbMReDq9Ra0thXa3j2qgb+qa/jN//wqHt2UJOzlw+snG7hzSMLrr3/PfW2hbYfNyfeO4dnx9orHpiRHOQVgF/fvnQjLLj8F4DMAQCl9mxBSATAB4Bb/JkrplwF8GQD2799Pa7Va6h2+Ot8EXn8V99x3P2pP7nZfLx+cxLYto6jVHgMA/OHF93BjsYVa7YXUn5EWL88eg3HpCh5+8jm3MKVI/MHF94Cb9qncu28fag9sEb6PfvdbACxs2r4btdr9vt+dfeM8cOIUPv3iC7Zn/M1J3H3vA6g9sbPw/S0Kk5OTqNVqdme/V14FAKiDo6jVngUA/NaHb6MyBOzYMIArzRnw19MfXzmIRTRQq33SfW38xJsYrCio1Z4GAJivvYy779iFWi2YQgJm6xow+Qr23HUPas/fGbufi0evAYcP4/lnnsI9mz2mtuXkm6iUvM9jeKtxCtXLl/Cpl17CwGvfxpZtO919YMc8d3gKOHIULzz7NPZM2P3WlTPTwPvv4KGHP4Gn7xpPehojcfaN88DJU/jUiy/YPuxLs/hXh97GvXsfRu3+zZF/Z1kUje98C/vu2YPnH9sOvPU67n1gL2qPbg+9t6mZwMvfBgXwAy980pfkZmDHXAT+dOoQ5ukyarUXfa8/Z1j4/VN/jct0E/7n2qO+3y21dEiEYLBcTNCfb2i4+u1X8IXn7katdq/7OqUU//SNb2NgYgeGBm8VdsxRSCLLvAfgXkLInYSQEuyE6TcC77kM4NMAQAh5EEAFwIpUDqhRjcNMf5ZcpMOuFJieuFLDeHXTAlMPsrpl+A6IveZzZ3q7RMSauyqHW00YJhXKMkyvppS6YwdFSGWFdLbJa+5A9MCOetvAYNl+byUgFTGwBmf+IqbkeYAkCHbFTJqLWWoZMC3q09yjrkte+luNpGqwDQlDSZHw/D3jeOvcdMg184/+/UH8wp8dLWwfmN6+f89G3+uEkFV1zHQM7pRSA8DPAHgZwCnYrpgThJBfIYR8znnbzwP4aULIUQB/DOAn6Qr5jlzNvZNbRpagr1KFKruwV6p3tGZYqLDgHvHAopS6Dzyx5m6ipEhQZannfO6sGnLbaDXgc7eDsyyRUIJdt6jPGgs4CVXnmPm+KiKwgqQkLSxEbhkgemAHn8iNDO7ChGq4yjYPGroJRSJe/51S5+Qo4H0ffrdMVH8czullFBcSbi218Mlfey00MNwwLdcuHcRzd0/g+kLL7a8OADPLbbx7cRa3FosbX/jexTkoEsGjnFOGYceG6qolVBOtQyil34SdKOVf+2Xu55MAni9218RwK1Q7tB9QV7FC1QvuK8fcKwrBokYjGRJ/PkTMvaEZGOQCClBcYm6lwdw/d4wPuCXdgBMkVUWYPBfd5FXVc8vE9XIH0g3rELllALunu6hClU3EAuyAGlfE5Gv5m8B2mAZBt1BFUMUrAusIuWGg5O1TBNvng37bNAGoeXbZxeWZBi7PNnDudh13bRpyXzcECVWG5++ZAAC8eW7G/ZvXz9wGpcWuYg9dnMO+HaNC4rBzQxWvXF9EUechDj1Xoeq1/BW4ZXxFTNKqtSFly82VmteomxRlWTxekIF/kM0LrJD1tufpdpti9YgVkq1E7hgfRF3zqh0buonBsmy3mgg+7M3wTV7huio29PjgTohd9JTMLcNaBQSZu1iWaXBBlX/g8GjpJiTib2lQNHNvBtxClYQrOtbnZwPH3KMkl3ZCp1dasG2J5DhVIMsAwJ7xAWwfrfg6VL52+nah+9Y2TByZmsf+OzYIf79jrIrpZS1yBV4kei+4R7X8Na1A+wGyajNU2YVxYyWZu+z9LHwPJ0FFMXd2I0sSQUmReoa5z3PMHfBaELAgaT/Ig7KMFfI780VMzOMd1X4AsHXaZEVM9jaDrYOHy+KBHQ3N9Jh7pOZut/vl3VeunFZgERNfAes2V+uwfdYRcsOA2pEo8A+KIoN7O2JovMgKyUAIwXP3TODt8zOwnOHnr5+xg3tRtuDjVxehGVZIb2dgdsiZZj+4h+C1/I1vHLaaPndthROqmiPL8J8VBH8+hO0HNBMDnBugokg9xNw1lBTJ7UC40NRhWrZENaAqzoO8c4UqH0iDpfciqDJJzNxVmUAKfF5UZ8h62/A095KMpqhCVQ8XWLHeNUV187Qfjvw1kUyWYcx9bKAERZagSCQyOPLMvcgW3B5zDz/Ug4l0Hs/fM475ho6T1xdx5Mo85hs6hitKYQ+egxdnAQBPRDJ3m6DMtFb+3uu54C5LBATexBUGw6KQ+Za/0upNYipKlqGU4j8cuBSqMNVNC2U3oRqluduvjw2oWGjqIUdAo+1p7oAdKHqliGmhoWOsqmK0auuUC02da4RmJ1QptS16DLpphWx3LKFqO2XiZRnAZu6JgrtuhfR2ILqne1M33e+iqkpoRVSoBlcVRWvu9jAQ7xxJTv+dTiu62boGWSIYcR5eceeJJxArIcuI5dno4P7c3bbu/ta5aUx+eAsSAV68b1Nh5/TgpTncOTGITcNiSzRj7tN95i6GRCBoFBVuP7DazP3mYssXYNLi6nwTv/T14/j2CX+1q2ZYqDrMPcpxwB5k44MlmBYNzVIN9lHppSHZ8w0dYwMqRnzB3auuZPILz94Ni4YSqhVVdpNnTe7vo5BGlgk6ZYDo5mH1treKqqqyMJi2IoI7IUUydyO0cimrnVd0cw0dGwZUVzKyh4gkkGXM4shEnOYuskIybBmp4O5Ng3jz7AwmP7yNx3dvwKbhciEPHkopDl2ai2TtALBluIwv/eg+3N+hSKwI9GRwlyV/bxlKqaO1rWxXSMuiwuDNLxGn69ktVZ4e7L8J7H4Z9qol6gZhwZ0VUQWTqg3N81YDtrOjV5j7fFPDWLUUYO4e8xbN1Q0m2AGvw2JbtxIxd1WWXG03Dm3Digju4ra/Tc3AgLMvwX43DC3d8unhgK0ZlxWpMM1d1PI4KsHLY66uucO9Aftaiva5W8Kf84KtYIOJScOKtkIyPH/PBA6cn8EHVxfw0gObnXsh/76dn65jtq7hyT3RwV2RJfzEM3dg29DKh97eDO7E/8Rmgd4/rEOCadFC23z+4n8+hn/81fdDr7cNC2MD9o2cR3dnTDp48+qGBYWw1Yj4eBhrZcE9qLvXe5y5jw54ssyiT5ZRhANcdFPQW6bkjdpz/16N1tyTumU0w/L1cmcQDeywLIqG7jH36CImMxTcAeehXBBzb+nh3jqViJUEj7mGP7iXYsb/8a8Xqbmz+z/UDTQmocrw3N0TbjCv3b/JHYKSZ9UNAMev2l0nH90V9revBXo2uPPM3Z10L/tlGaDYC+rk9UVcng1PdNFMC3dstBMleQqZ2I0QtKJpTvVtXLDxmLt90wWDe1Bzryhif3U3YqEZ1tybIubOyzICSxzzjDd1UzjGLohyTllGNLCjZZig1Fsx8FWzPJq6iYpg34p8KDcED5BgW2QR5hoaNgx6Pu14WWYNrJCCFgc8nr1rHBIBNg+XsXfbSKpq5DiwQRy7nViw1ujJ4C4RP4MVMne32Km4C+r2UlvIUDTDwh3jdv+PPIVMTOsM3ii6aUGWnMRVlBXSeX1cwNxdtuhLqEbfkN0GO5jYnuqqKodlGYE9NqorJGCz4qSyTFK3TFLN3R13yAV33aShIBVMdjKUlc7MOilEjpwqVwsQBVtz52QZNSahyrcfKNIKGeGWibNCMowOqPjsw9vw+ad2u1IXv82smJprYHywFOvAWk10x16khCL53TLspvZp7hFDPbLCsii/xQ6VAAAgAElEQVSmlzUhK9AMC1tGyigrUr7g7lxcPHMyLQqLAopT0BI105OdA5Hm7rLFst/2Jip26ja0dBMt3XJZ+2hVDSdUpfBgDVFfb7cCU/eCu0j6YEjjlikJgvuQKLi7E7G8ClV2nPz+itwy9jEUZ2ENFjEBtotKJBMxUEptzX2Qk2XkhMx9NRKqgUlMUfiNv/e4+3Oa9s5xmJprYqfjhukG9Chz9+urTHfjv9Q0k3SSYN7xVosuYs20rXDbUsygFMGTZfggxY4NUGOYu+Ey97Asw0bsDfYgc2fHwXIao1UV842g5h5OqAaL2gA+oWo6wVMKedN5pHPLhAOxKtsrDV6WaeiehRPwvOvBgBqnuRfB3HXTgmFRgSwTr+m3Dfvv2KqE7VMSzb1QWSaiiEnUMK4TkgwcSYKrc03s3NAdkgzQo8FdJv4luOkyd39CFQgXO2XFbWeAQfDCN51Kt5IiYetoJVeVKgu2ok56rMFTZIWqc5zDFQUlWXLH0gF8HxU/c+8FzZ2tLsaq9kMryNyZzx3wXxO6JegKGUiodlo+qzGMlEeULAOEm4e5s2w5KyQAtLSwLLOSzL0RYQWtdtD02fXIV+PGyzI8c1/5IiZD4JLqhFIBzN2yKKbm+8w9N+zgHpZlgi1/geKYOwvuQebMLoiSImH7aLUYzd3XSc/+WSbx7g12PlRZwuiA6uueyKYw+ayQCbTVboBXDWkz9xEnuDcFPnd/QtUSJFT9skycJAPE5zh42G6ZmODe9neyBPwJVbZPPFq6JUz2JnGzJEFUQjnKvcOgc9c7Q7wss0LMPTKhmkyW4VGE5j693IZmWP3gnhdBWcZNqHJsQo3oQZMVt5ftoN02LJ+9kl1kqixh21gFNxZbofazSSFyyzBm4sky8UVMskRc6YKBlzAYyjH2tW4CaxrGa+6LPHNXwz53i+UpYhKqcfNTGcoJW1jYzF28Lbt5WDih6gb3kufgYTBMe6C0WJYplrmHrJAdVnTselR9zD3aJ942LFcOXJkK1TBzl1PKMkUw9yuOU6Yvy+SEHOgCKGTurixTLHOn1L8UbDtJopIiYduoPYNyejlbIVNL4JZhF5wiASWZRCZUWRBSJQljDrtlqHPDsRlsbbX7mTtrxcBr7gtNHQ3dQEmRoMiSV6HKdFhuFcOD76oYNz+VIblbRmyFBGzmvugL7v4HrajNLqtzEAb3gph7wx2OHZBlIloQM+ii/FbMeWrrllvMtSqae4f2AyJ4mnv2/Zuasy3SO/rMPR/CmrsjXQTaDwDFuWVuc0ODRUmisixh26jd2CprUlXE3F3NnZBYmYD3+idh7hW1mMKNlQbLHYwNeJp7XTOx2PS6XAatkCJrLMA7U6zIhCWPxG4ZQ+yWAWyvuy+hKrBCAv7e+izQV4RWyGzMfa6u4Y0z3nA0T5YJtx9IpLkrfs09cliHYWKgbOdFimwHwr4X/n5gleppNfdyAQPjmcd9x1g/uOeCTPyMPJa5F+Rz54O7JmDWjLkD2b3urhXSV9XHuWViZAJ2DlSZYHRAzNx9PvcC2AoDpRT//C9O4NCluc5vTon5hg5VJm4wHK3awejmYsst4Q9O53KlrCBzVzwJpKFHj9hjsN0yCSYx6ckTqo1gQpU9cHjmLpjC5B5DxoZvf3rwCv7B773rPmiirKAVRYZmWpHSortC5GWZmCIm1lRNlUmhY/bYtoTybErmzpLDeVYWU3NNbBwsFTaHtQj0ZHCXAsyd15sZlKKZ+zLP3HkHAJdQHbOZe97g3o6wQsZXqLL3Sa50wRDF3IFiBj8YFsVX3ryIl0/cyL2tIOabOkarJbdJ1Shr87DQcgNjMKFquAHIf5PbEg5xE6pJ3DKdbnhKaaQVEmDBPZzcZkFVlFCNq561NfH0QajeNmBRb+ZA1CSqTqP2WOM6PriX4oK7I1klbeWQFKKEqiHIvSVBuYDZtFNzja5KpgI9GtwVqXP7gVJAh80LvywjYO6yHVQrqoTrWWUZ56aOZO6xPnfvHIxVS1huG+7f1rWw5l4kc2efkzXXEIcFpyMkA0us3lhousE5mFD1VnLhy7viNMZKklBlMlhcfyLDSd5GM3cVLd1yz1FTs/31jIiIgjv7Way5Z0uEswcGIx7NKLeMO40pIrdjhR+crHGY6Dy1dQsVVUKpoOZcDG5w75B7S4IimPvVLrNBAj0a3CVCfLIM09yDY/aA4nzu08saxp2qPJHmXlIkEEJy2SG9ClX+4eGsSpyxb50mMamy5EoX/MQiQrxhDECxzJ2xuZllrcM702OuoWGsGg7ucw3dZZ2hhCp7IApcE6yXS1PQNCsIFrDjVn9uziXCCjkSqFKtB/z1rH8Mn1BtxlTPVhS7XUFaRxa7tljvo6jPqERYMxl0jswwuBWegmuTrWqS9ulJCjehygVkI+Z7j4M7BCWj5k4p7boCJqBHg3swoeqyVpEsU4DmrpsWZuua+2QWDSBgCaZtY5XMQzs8WUbM3JM0DlMk4iYfmY2w0bZbzPLVmEUOyWY32my9+OA+H8HcAU9SYCyYBTzR9cDA3CCNBMydsdM4rdidnxpjhQTg07r5h0qVc/AwsMAq6jSZNfnHrllGPCKtkB3mtLpWSCUc3EXMvG3YzD3pVKukiJVlVpm5315uo91lHnegV4O7JE6k+NwyBVaoMkbKbE78zd42/cF960g1c5Wq65bxjSbjZZmYlr8ua5F83RMB4Ppiyx10wdBpan0asM+eWQlZxtHcGUZ8wd1mwK4zigV3yzsXQVRVGctt0x3RF4ckN707PzXKLcOtNAA7oTrIMXfVGVPn19yjrZCdZJNO+8laUjcjkradg7s4oQqIr6WWbjP3pM6jpBDJMl4cKF5zn1lu4/BlsWFgyvW494N7bkRWqMph5l6Ez53p7WzZJWTuzsW+bbSSeSIT265meBZF3lesJmgcxtwygK1XNzUTk6dv4cX7Nvne3+kmTgM3uNe1QvvnA3aFahRzZ8w7WNPgsksBgyurMmadgSqd3TKys72Y4K4z5i6+lR7YOgwAbmCoa4awE2OTaz8Ql1AtZ/zeXFlm0UuoSiS8353kOr4dhrtPznkSyzK2kyhptW9SiGSZODkuDkkqVL/8+nn8d7/zjvD69myQfVkmN0JuGdfnHq5QDY7jywJWnerKMiKfu3OBDJYVWDRborIl6CnDtiMTx5XQoXGY4hQxATbrffX0LdQ1E597dLvv/UXO42TnoG1YbvK2CBgWRV0zfZp7WZHdABTyuZsBWUbI3CVXPkosy8Qy93hZZtfGAezeOIC3zs0AsIMqn9gGwp0Y4xKqlYzODvb+G45kyNovMBeSt32vFkAEPbBS5X8WNRxjPXLi8kVZ4FaociQvrxUy7pxeW2ih4dRXBNGNBUxAjwZ3mZBAB8CVrVD1mDsL7tGaeyVHQQS/ImDMiW8/wG4QEXvwysKJy27nGxq+cfQqNg2X8fRd4773F8nceUZWpDRTdxyEY1x7WcBj70HmzvIruhXN4Kqq7AX3BEVMQPxNz77nKOYOAM/fM44D52dgmPbDrxqQg6ol/4CMTglVIAtzD8sywQIm/jMzyTIRmntZkRI3YUsKUT/3qPqGTiCsQDBm/6adGHBbcH1PzTWxYUDFUBd53IFeDe6S+Ikt8rkXobmz4M6WXb4ipgCTyWMx5P+GMadgQpVScb8cw7Jb3BLiBfepuSZe+/A2/tbD20Ltb93ldyFWSG9/ZnImVa/MNvDKyZsAgLpub3cskC9gx8e0a/Zds+uA/T/YOAywHwisHUByt0z0OerklgHssW5LLQPHry2iGZhlC4TnlnoJVUGFalbm7lxPS20DSy0dTc1w+9rw6OyW8UgEQ1xvlrbTVK14zd0MfWZW5g7YFeZxhIwFdZHdd6oLnTJArwb3iDF7/AXHmEUROt/tpTZGKorbw1pohZRZcM9uMeS3y372ae4xwcae+m4fvyJLGCor+PqRq9AMC5/7xPbQ+92HUIGaO5DfDvmVNy/ip//gIP78yFUvuA+Ig7trhXSHdQTyFALmzicQO8sySRKq8bIMADx7t71qevPstDPLVhDcue+hrdvWVdFqICtz5yW/m4st2woqSCh7mnu85dZvhRQTGt2pdK04Vsgig7vu1jSENfdOk5hE6DTfYDo2uHdfARPQo8FdIn62KMqSu1WLBQT36WUNm4bLwuVnWJbJx9zZTdPikqsAnAHZThAzxLIMn0AcraqYXrbtm48JBvaWi2Tu3DZYsjIrmGXwn/7ZMZyYsQPSWLWDLBNInhtm+GHPwEsdnSpUk8zWTCLLTAyV8cDWYbx9bsaZfuT/3EpgjmpTF+vhQD7mzqZ0XZtvRVpBO8oyXBfU4D4Fg3ebW9UkHXySFFogeQ5wK7aUCVUg3masGZbbq2l6yX99ex73fnAvBErUgGyRLFNEQnWpbQd3d5JPnCyTg7nrlmudE2ru7OEiGFdmzwz1vk4WAP/2o9vFQaJA5s4Hv+mczL2hm9gyUsb4YAlfP+vvCMkwEmDuwe/aEBS1MVR8wb2D5u4+TDu7ZaKskAzP3T2B9y7Ooq75B5UD4U6MLLiLUM6suVvYM25LBzcWWs6M1vRuHJHP3UtI+v+GXVsV1e65X5Rbhg3Isfcn7JpLa4UE4tsWz3CEJXh9Ty9rjse9L8sUAinQYU7YFTKwVM+D28ttTAx5zN3ncw/IMvmYu4mRKpN+RJp7dL8cw6I+xsICYtAlw5DVdSGCT3PPG9zbBraMVPDbf38/mOQ8GiHLsMRkcOqWl1iLZ+4dZRn3YZpElom/lZ6/Z9yZBRDuxBiUZZqaJWwaBmRPhLcNE7ud4H7dcX6IHm5JrZC+9gMR11KLOzdF9pbht+ML7m7b66zMXXzMfOuR2wHmzpwy3cjcuyu9mxBBzV2PqVAtyi2zabgMRSIgxM92NUdKYezYvdAzFAe1DW8QtMfcLUjEbrngzoUV3CT2BBovwOyZGMRy23B91kHY+1yszx3IL8swTfrhnaP4Hx8t46I1juGACyGoucvO9+I1DovuLcMH9KTMPUkRk6ialMdTd26ELBGYFhUnVAONw0TtfoHsFta2YWG4rGBiqIzrC027x43g+EuyBIl0tkLyyWrX5x6UZVhiuOAiJradgZKfbYuMFUkRp7mzgC6RsObuetz7wb0YsPYDlFIQQiJmqBbjc29oBpbbBjYNl0EICbU31QK9vLMmvCilaOlmKLhrpuXqm3FJ4uBg4F/53EMwLCqUZAAIjyUr2M02WlVzu2UamoEtw3Z3zSe2KPj52mOh9wSDO2AHm2CSrVNCtWOFagK3TFLmPlxR8cjOURy+PB/u51LyFzHZNsV45p5WTmvrFsqqPcT9+gJLqIY/gxASygHw0J3B43wrC88yGpBlnHNTUYstYmKy5GBZQUNrw7KovZoXFDMmRVzClwX0PROD0cG9i/q4MySSZQghnyGEfEgIOUsI+cWI9/xdQshJQsgJQsgfFbubfjBp2e0lImj1SQiBIpHczH16yQ5Wm5xkVDnQ3U4zzdDgAiA9s2LdBVngcmUZg7oMMs69oVvUl+RSZClyac8QdxOnAbtpt41WCpBlOvd8YZITn5hUZCKoUBW3H3B/LoC5B4vY4vD83RMAEOr5XQ18D1F6OJDt+vLaEktOcG/G9taJm6OqmzSUsIxaTbR45r4CsgzLXTAHj6iBYFLEtS1mzP3BrSMhzf3qfMNx0qmiP11TdDwLhBAZwG8A+CyAvQC+QAjZG3jPvQD+dwDPU0ofAvBzK7CvLhhp8CbveHZBHopMcidUWXXqpmEW3P1+WCbLMGRNqLY59sv/vWaarvYb597IOhi4SFlm62jFl3zKAjvhGM+oP/XAFvz8D96H+znJiR+9GNcdkMkdikQ6JkGTzNZMYoVkqN1vt4BgrhUGJsuw4rSmU9UpQpaVId+WmGfukcFdiZ7GpBkWguMLyxHniV/VJGmfnBRucHceksFcSyZZxmlbLML0sobhioIdG6q4vdz2HcO1+RZ2dGEyFUjG3J8CcJZSep5SqgH4EwA/EnjPTwP4DUrpHABQSm8Vu5t+yCTojhB/qaqUny2wpzYL7sEnfEiWyZhQZctsN7hzzJ0xpTj3hm7S1JV5lRiHQBqw/dk6UsFszv4yDc0eyxaH0aqKf/LpewNjFSVXjolbnrtDMjqwdrZNoFNvGdN5b+eAsn/PRrz8c5/Ek3s2+PepJMO0qBuc4kYAqrKT90nxvfGTnbaNVbHUMqAZ4gHcgC0TRXULNSw/mQGiK3k9K6QcW4CXFozcMBLAvh/PCpmBuccUMbGc28RQCZphYanttSC4OtfsSkkGSBbcdwC4wv17ynmNx30A7iOEvEkIOUAI+UxROygCu48YQzMjWryqioS8Y/aCwT2kuZv+4J6XuY84y7s2l1ANau5it4yV2t/badJ9UrD92TpagW5S30DoNKCUoqGZHZm7CLYE56zkBEk/BpZE7NR6AEjafsAur4/KbQRx/9bhyH4uTAppxTB3Qkjq741n0GzOLxCdUK4osm/sHw+bbASCO7NCBvbJk2WkRPmLpHATqmV/w7IokpcEsQlVxy3HVlzM604p7cohHQxJ7iLRmQpGFwXAvQBqAHYCeIMQso9SOu/bECFfBPBFANiyZQsmJyfT7i8AwNDbAAhef+NNjJQJzp63dbA3Xv+e78axDB2Xp65hcnIm0+cAwMEzGgiA4wffhkQI9FYT12603H2/dqMFrUXdf2tOgDn10RlMGpcSf86Nun1hXb98zvn7s5g0L2PqegtG28LysoXzRw/b+3T4CIyr/q/u9nQTbROpzqnWbOLazUbm74Hhw3P2+V+4bh/vt159A1sH07MnzRlCcePqJUxOXsfy8nLifTN1DVeuXsfk5CxOX7D98QfefhNVxX/5fjhrBxxiah23zb7L02fs70KEcxfbkGHlOoeXL9v7++r33oBqNDC/LGF+Jnr/ZJg4d+kKJieTLZBnmva1deHcGWwZ8L6XqYvnMWldCb1fazZxXROf+yvX2jB1M/Q7VQLOXrC/N4bD1+2H/LHDh3Bp2j7vr06+gaGS/ztJ8z0DwJk5e1uNhVkAwBvffwvjVQkfXLXP4/sH38XUQLrrb/Z2G0v18HEBwOWbDewekXDtfB0A8Mob7+D+jTLqOsVy20Bz5homJ2+H/i4OaY85C5IE9ykAu7h/7wRwTfCeA5RSHcAFQsiHsIP9e/ybKKVfBvBlANi/fz+t1WqZdnryyisANDz1zLPYOlrBe+3TkC+cx0svveR73+CBV7Fp8zhqtUczfQ4AvDz7AcZv3sSnnG2Pn3wTQ2UFtdrTAIDfPfcO0DJQqz0PAHar3le+iR2796BWuy/x55y+sQi88Qb2P7oPXznxPrbvugO12v344ysHsYgGhoYs3HnfY8CB7+OBvftQ27fV9/e/9eHbGARQqz2b+DN/8/TbkKR0fyPCEeMj4MwZfPKpR/GVE+/hnoc+gf17NqbezmxdA155BQ8/cB9qz+3B5OQkkl4jg+++honNY6jVHsMpnAM+PI2XXvxkiAFvuDIPvPsmNo4Oo1Z7IXabpvNd7tp9J2q1e4XveXn2GAbnbiXeTxFm358CTh7FY/ufxsXj74FKGu7avQO12kPC9w+99V1MbJ5IfF2fv70MfO97eHTfXjy+ewP+r3dfAwA88tCDqD2xM/T+/+/sAbR0C7Xac6Hf/dm19zGsL4aOtzL5MjZv8+/zrYNXgKPH8MJzz8D66DZw+jieeuZZbB6p+P52cnISdOte/NG7l/HbP/GEz4kjQuncNPDOO9izcxvevTGF/U89jTvGB+3P++AYnnv2mdRFRX89/wFOzN8Qfo/1yZex966d+NT+Xfj1g29g1717UXt4G05eWwS++wY++cQ+1B7Zlurz0lzbWZHk8fYegHsJIXcSQkoAPg/gG4H3fB3ASwBACJmALdOcL3JHeXgJVW85Jkom2gnV/LIMk2SAsGUqqLlLkj0OL/UwBd2zjfHSj+1O8Fe/CnvLWGEXQyeU1fT7KYLuJHOZoyhrlWq9nayhlwh88txrfxxthUzyGbJEIEsEmqAimIHJMnkQnKMal1AF7GskzffGyzKbR7xrOU6WaUbJMqYllLvKihxK9AfbD/CvBfHWuWm8cvImjl9b6HA04YSqa4GNqW/ohJIsTqi2dBNLLdsKPTFst8Fgdsir893rcQcSBHdKqQHgZwC8DOAUgK9RSk8QQn6FEPI5520vA5ghhJwE8BqAX6CUZtdCOsDT3JnGGhHcJZK7K+T0chsTQ15vk+CgX80M39xZhhjztjHeomhr7vaxxVkhDdNKP4GmoKHFzEEx7pynrI4Zb/Rbes1dlSTPChmjvVZTBHcgvucIUExwZ3mAlm7izJw9JWr7WCXy/fb3lkVzl1FWZFc7jkyoqtEJVd2kUJXweS0rUqhwj28/0KnDJuuT/trpzvIG+z6GysGEarRLqhOi7lkWyCeGStg4UAIhnuZ+lfVx7+GEKiil36SU3kcpvZtS+i+c136ZUvoN52dKKf1fKaV7KaUPU0r/ZCV3WuSWEd3IagEDAuptw9enWVjEFLKGyRnGoHnMnU+Y8dazOPdGsHFYElRUqaCukBQlRcJGp+/6bFbmrjnMvYNbRgTb5+4xd8VpfxxExWlzmyShCtjulLgWFm3dcic2ZYXL3DUT//Eju0ndjwvkEobUzJ1LbAJwk6pxPveoCms+wc8jaBEG/CuGTl1aF52Gca992DmPwLYxEHDLZJ2hyvZRN2loghpvqFBkCRsHSrjtXN9X55soK5KP/HUTerK3DLu2DLd4QWwDLMLnHiz2EPrcBaPKUg8w5thVReVlGW/7cT53+xyk9bkXV8SkyhLKiozhipK5SpVJAZncMrLEzVCNPhepmXuH1Q0rDsoDtk/fOn4DH81Z+NlP3xu7esnM3B2P/1YW3COZe3T9g8jnDkDYXoC1Li7JUseCsCXHYXV0ar7jwBePubMxiJ0ncHVC1L3Fgjtb7UwMlV02f22+hR1j1cROqdVGTwZ3KSDLRDF3RcrP3Ju6v8FSWZFDXSGDwT1LWT/fOpYPurzmHl+hamXwuRfTfkA3LLep2fhgKXNwz6W5S8RdlkfpwoCnuYumEInQqQ95IZq7c7xffecSNg8QfP7JXbHvT5sr4SU/ANjuBPdIzT2mQtWwaGilam87fC3xNtFOBWGLLR2bhsugFHj9TLw04/WWKZK5i+tTWP6I5d0mhktucJ+ab2J7l0oyQI8Gd1dzt/zL8CCKmNvY0Awfiwr2yBDJMvayNn3vD8Bj7nw/d6a5e7qlwOeeSZYpyuduuVW040PlzKP2mOYeLM9PAkUiPgYXxdxVWYIqk8QPEFuW6RDcE0o8UWAM2qLAf31PqWMRTtrvjZf8AGDraNXdTtT+tLiKWR58DoiHaDXR0k03aHbqjb/UMvD0nRsxMVTqqLu7RUwBzZ3lXLL43KP64zDmPj4YZu7dXMAE9HDjMMBLoJhRzF0muSpULYuipfsr+ezEUbwsk425e0tnu7d0dBFTVEI1LXMvK1JhY/bYvo0PlnBpppFpO0xzD/Y7TwJVltBw/j7Y2z6IL/3oPjy+e0Pk73l06mbY1k2Uh8uRv08CFmQf3DaCp7Z1LgBLO9Uo2CLhbz60BReml30FTf79kWBRlkvx31dRskxZldyVF/+5jJB0mmq12NQxWlXx4n2b8denbkbe0/w2WHdNfgUPZNfcRfs3vdzG2IDq3uObhsqYXtLQ0k1ML7e71ikD9CpzZx0fuS9VdMHxOmwWsKWpT5ZR49sPANm0bL8swzF301sZyBJxplCJZJn0VsiKape9522uxneuHB/KLss02s75zsLcfVbI+FXMf/vkbty7RdwKOYhO3QxFbqm02DhYwo9+Yju+9KP7ICXQb9Mzd39C9e5NQ/i1H3808gEYN0eVX6XxKAkGYLcNry99VPAE7ErPxZaOkaqKTz2wGQtNHUeuzMUcj1+W8SpUvTnCaRHV/Oz2UtvXC2hiuIymbuLsrWUA3euUAXo1uLvM3RuILHTL5OwK6bk3eLeM7AxdsD+7LdDcs2jZ/oRq0ArpbT8q2AT7uScBW6Y3ckozuslr7mXMNbSQ6yAJ2PlO6mThwdtejYgEexZ0cly1dStR07A4yBLBv/n8Y3jijmSribQrQ17yS4K4tsJRrixR+b4ty3Q2A+iWvd2RioofuHcCskTw6ulo14xuRjP3LKwd4IK7Hmbum/jg7vx8bMr24/eZe8EIae6WWHPn7XFZwNwbAwFZBrAvRkopNMNCWWCFTDusgwXzkmK36mUMh9kMGdQI33WczhyFsQHbwjVf11P9XRD8Un3jYAmmRbHQTL/NhmYPqciimSoS1zjMtDJ5nUUQMVIebcHKbaWRVXNnbpkk2wfEAzuirZDhIiCeucfZeBvOIPThioLRqoon7tgQq7trhn2/s4eV63OPqHdJAnfgSNAts+wvYmS2x6NX7M4qfeZeMBhBdRuHRWruktvrOQu8oppwcG8bpisLiZh7VBFIFNpO4lSWiK8Vrx7QOKOSxLolvuniMD6Yr+jI/Wxu9ZKnkKmRoN1vFPw+dxrplkmLjpp7AVbItEi7MmSyjMjlErV9IIssE/S5C5i7YL8bjlTPZuO+cM8ETl5fdIelB8GkUCZD8o3DshADfv+Cq5XpoCzj/Hx0ah4S8Wyl3YieDO5B5q5HPLHVnBWqLLgHfe6AHYyDw7G996Rn7m3dcnt12w8HT3PnKwKjgo2RgbW4RUc5pydpXEJ1IkcLgka7c7vfKKjcg9xOqBbH3Du7ZVb3NiorMowUuZK24+jq1LOFIa5nvMgdBkTJMt65ifO5Nwz7Hh2p2A/2LU7vmajVH7Mfs2vOk2XSExx3/wWyUUMzUNdMH3NnP390cwlbRiqZP2810L17FgO3QtWM19yVnFbIpqAcnvfDsgs1VKGaibmb7o1QUWRfy3rMp5kAACAASURBVF9++yINmFKaSWdm9q68o/H0gCwDZHtgJBnUEQWZe5BHPeyzII65u7JcTs09Ldwh1gnZO699J0G1FB3co3oYido0tA3TfVDE9ZbxZBmbuTOLY70dXUhVkqWQ1GOYRTB3b//YFDa+ApVd3xbtbkkG6Nngbv/f8DG18KHYgTAPcw8X1bAArPHBPXBzx5VvR6HNBYmyw9xNZ4JOMKEaPCa2gknrc984VAxzt2UZJ6HKZJkMXveGZmYqYAJsP7ovB1MQo4pzy7DXV1uWcQlGQt09rRe/oyyTg7mL7kcmy4xW7aDOEqXLbbEtlMkybHXGFzFlZ+5hzT04hQ2w78UNzpjHbk6mAr0a3F3N3WPuQlkmZ1dIdnHzsow7mMAwueAe9rm3DHERSBR4T3BFsS2K7OGiBph78CZi50FOKUUMluyGTkUEd5e5DzDNPQNzbxuZmoYBTkKVm6FaFHNXZUk4+QpIPhy7aKRl7rajJ/k+lhVxQpVS6qtpCP5N0FZra+6BIibBPjcDzH3IZe7i4M4casEHRpw3vhNERUzB1gMM7N/dXJ0K9GpwD1gh49oPFKG5i5h7W7fcVrDhhKoMSsUsJQpt3Ru0zRwGrN8GvwwuCSommdacNolICLHbBeQcas3f8IosYbSqZnpg5GHuwcZhRWmhcczdsxh2O3M3U+UFGJkJJkijDAT8a/y5auuW+yCKa5/sae5BWSaGuQtkmTwuKZEPnzUI2zwsDu59WWYFwOK4zjcOi2DueTR3t9eJKtbc21Gae0Qpcxz4pTO7EVlw528mkQbsjhnMcGFvHCphNqdbRgsE09GqisUMVsi6ZmRqPQAEE6rpbaFRiLNCesVBa6S5J5T+2inzAp4VMhjc7c8T3WsinzjffgCIbp/cNOx7lR0XY+5LMcG9rEhOwZLfNZd1xSbKCdxeaoMQT2dnmHCCfV+WWQEwlm5yFYmiXuZ5u0I2Y90yniwT6ueupLv57PeaPlkGgGsFC8oyUcw9i868cbCc3y3DNQ4DgJGqkmmOajMHc5cl4rsesgxsEMHOcXSQZVbbLaOKmXUU0jY3qzjvDQ7sYOchSpYBAsw94CSKap/c0CmGK6pbWdpJlgm25NC4RHramQbe/gsSqsttbBgohe4rlmDd2WfuxYPFEZ2zQImHdUgwLZpK++bR0E2oMvExZ/ci9iVUg26ZdDef/V7vBnSZezusuYuCDZMj0iZUgXxdHBl4nztgL68zMfe2mZ25O43DbOdQ+mHhUYgb1rF2skxK5p7VLRM4bha4hT73QHCklIZWDFHtkxsGdW2QQEJZhvWs4arQzRzfu+jhNN/Q3OQpjzs2DqCiSn3mvhIINg6LWoarbjbdDn6WRfHP/+KEPVMyAZqaGSqF55dv0T739Mzd34cjWnOPS6hmY+5FaO5+WWakorrDF5LCtGiovXIasGO3k3rFtR8oKXYTLZGnfO1kGRZ8V8gtE+FzZ9dZSXCvBaVIUbI5quFZw/CSqQDcZOlylBWSIxMqR3byFDGxe4zPYyw4zcyC+MLTu/Gdn3sxc/J/tdCTwV0KMPcorU0JJFxuLLbwlTcv4o/euZzoc4LtfgGxLCNq+cvekxR8NV/F1dx132eyz4pMqGbR3AdLaOpm5MzMThA5KEaqijs2LSmYMylPhSpg3+C6ZWVaxYigBhwZPKJkuZVGVB+UKKT1ubM5wEErZLws49esvTbDPHMXJ6cbOsVI1f+9D5bljglVti+a6clxWSuTCbErw9vc/kUF97IiY/d4ugHca4GeDO7sOu2ouUv+YidmLXznwmyizxG5N3xumRgrJBA9DFgEvgEVuyGWW2JZJniD5BkMnLcFgchBkYW5N5wbOWr0Wyew71o3rUx9dqIQZ+FbK809LXnQuFVh8s8Iz0SNC+7BhGSwE6X9d0RoK7VlGX8QHSwrHX3uQFCWyc7c2THwxzzf0N3+S72Ingzu7OvrlCVnFwBjtqzi7cS1hUTBpxkYsQf4tbkoWSbKbRAHPvnEboglQXC3bxA/i3RdDBmZO5C9kMm74fmEqoqGZqbqyFl3B3VkDe6eLJMnsRaEG7QEFj7PLbW6skxa5p5lWpSoOZnmXHdxCVVXlhHkI6KYe1O3m4bxGIoJ7nyzNl6W0XO2nSgrsm//oph7r6A3gzshgYpEKizgYTc8Y7aspaxFgUMXo/tFM4iYO5846myFTNfcyZNl0rll3ArVDBe21+grb3DnmbtjZUvhmPGqgbNaIb38SrEJVX/ehofLTteIuSfX3NM3NxON2hM9yBn4ym32mfy+AtHJaRFzHyor0bIM10NfkYg7syGPFRJgg3g8wrjUMtxmZr2IngzugNNLJEHLX8C7KBtcgubAhZmOn9HQzdCszWRWyHRFJvb2wrKM53OPbxzGGHIWWWaj019mNmNSVRMFd+eGSCPNNHIMxwa8/IphWYVbIYEIWWaN3DJev/U0FarpZZkon7tQlpH9hKYVxdwF127b9CdUAVuWSaq5M6kn74qtzK0sGLHqM/c1gMpVn5oRDYNULskGeMx9fLCEd8531t0bbSM08k1xpiH5GocJWv4CyZm7ZVG3MAPwbohFkeYuh5e2ep4ippyyjCipzG7UNElVt2Asoywjc/mVqDmfWcAkl1jNfZXdMp4bK41bJt2tbs9RjbBCCoJ7JQFzVwXXLiMwwYRqnCzDa+68NTiPFZJtixEy1pGyH9zXADLXNyZyzJ4ryzjM3WGHL96/CR9cXYhkBgwNgeZuZ9XleCtkSs3dbUDFukLGyDJCn7sVfdN1wkhFgSqTHLKMIwlxqwsmy6wmc+cf5EVWqKqB1R8PTZA0XA2osl2dmUSWsSyaaRRgWaC5e8lzUVdIr3IbEK9qRFZIdo2EE6pydHDnrJCKFJBn88oyzv71g/sagv9SI8fsBfRSFsxfun8zTIvi0KV43T3Kd82Wl5FWyJSae3AMGmNBy4IiJlUO+67dxmEZLmxCCDYOZm9BwIIen1R0ZZkUhUwuc8/slvEe5Lb2WnBCtYvcMoBfH46D17kyrSwTDu5GDHN3XWTOA6fl5iPirZCMuYcTqqqw5a9pUZgcmeMnk2WZaeA7Bm6aFAvuY4Iipl5BDwd3rwtgXIUqwGnuDjv85L2bIEsE73TQ3UU+d4A94W3NXSLh4qFyWk3UXcIyWSaguQeCu31MXoLP1UIzBrQ8LQjYzRB0ywDZmHuelr+Ap/UWWaEKxMsySSccFYmKKidi7ixAp2XuVVUKyTJJfO5agLlXuAefKKHKCEAwcTlUllHXjFB1uR5YLauy5CN5eYrXSoo3TWq+0WfuawaWULWcnufiYR1sqe5YITUDJUXC6ICKfTtGY3V3y6Jo6ZZwWHPZ8QDzy0Pf7zNoovbfye6xqTLxZJlAQhXwBxvm988qReRpQeDe8D6fuyPLpNHcnXxI1vYD7EHOHB5FVqgCYlmmqZtQJFLYZ6VBJSFzFxUTJdq+4OHBioWS+dzDKwaR0ytallFAqffQDx6Pl1D1mgPqppjkJQWfUO3LMmsI1WnxalJWwCOeDgN4LLfRNt0E6TN3bsTRqfnIykwWJERM0tXcI0aOMU00sSwj0G4riixk7syaxy9v9RxWSACOLJNPc+f3cbCkQCLpmHtTMyGR7Po1s8K6wb3ASUyAmLkvrqEPuqzKifq5Z3X0VBQ53DgsZqXiumV05pYJX9Mit8xihCwT1V8m6FDjZRkzZ66FL2LqB/c1BOsC6OnNgoRqYMZinZNZnr5rI3ST4vBlse4eJxOwxIvN3MWMiB9y3Qki21hZlT3/euAGAfxMMo8VEnCCe0YrpGipLkkEwymbh9XbJgZLitsZMC2YJMXOeVH93Nl2RMU3800do2ukySa9vrJ68aslUUI1ulhOkSUoXL/2yPYDiWUZ+z4NJlWDJgZelrGZezFWyMWmjpIipV7xdBN6NrizJZ4R01fF9blbns+dVUDu37MRAHBkal64fa/db1gmKHGaexQjqqjiDngieIm5cGthQKy58zeJkcMKCdiyzFLbSNULh8Gzx/k/O23b34ZmZLZBAt6xs4CUxzXBI06WWWjoGFsjZldRZbfwKw5Z7Zps1COPOM0d8DNf0Wq0FOjdAnjMfagctkICguBuBIM74ayQ+RKqQebey6wd6OHgzpg705uFbhlBhSpj7iMVFSVZitSF64L5qQwuczfEmrv3noSau2AJW1HDAZ3/WffJMtmtkIA3S3Wunr5Nr5dQ9X922ra/dc3MbIO0P9+RZTTT9++8CBbn8JhvamsWAB7cNoxjVxYi2xEziIJsElQc5wi7vwBPc49KIPNWQmERk0PI+CTpUktHVQnfv4OdgrvjzlJkr94lqlI9Kfj2AwvNtXtwF4WeDe6KLEF3PM2AWGN1E6qcW4bvXVItyWhGsJ94WSZecweYlSwlc/cFd/tzJeK/8EXjzLzGYdmZO2APJ0iLoHuBIW3zsEbbyNw0DPBkOU9zX/kK1bVsLPXS/Zux1DZw8GJ8MV5WzV00as9Lnouvs7Iiu6SobYSTzSVZAqXwDdBZbBoYEGzPG9gR7G8TlmXYvWAU0n7AK2L6WDB3QshnCCEfEkLOEkJ+MeZ9P04IoYSQ/cXtohiKRGBaFsfcRYlNJst4Pnfe2jhQkkPZeIamG9zFVkjNiHbLsPckn5QT7gvOJ4x4iKx5nhaa3QoJZKtS9XzugeCesu1vXTNyMXd2U3tumWKZe5Qss1YB4Pl7JlBSJLx6+lbs+0SSXxKwWg2eoMT53AHg4Z2jeOPMtN1SQDCUW/SgZMw9CEbCQgnVwNxiNlOYUpq7voH34c+v4XdbFDqeCUKIDOA3AHwWwF4AXyCE7BW8bxjAzwJ4p+idFEFxJu/EMnfmczc45l7yM/eo4N6IkWV4zT1q+W8nvNJq7mHmHgyaIp97nsZhQL4WBKxDZXA6T2rmrpm5NHd2Xjyf+8oyd8O0sNQ21qzIZbCs4Nm7xjsG96w+d3b98c3DtA4rxL/z+A7cXmrjzXMzaBlmKBkpyhcttnQMqNHMPSjLBK2QTJaJiwNJUVZk6Kb9kPi4MPenAJyllJ6nlGoA/gTAjwje96sAfg1Aq8D9i4QiM7eM/WUn8bk3AgOYbeYuZpfsohZJBWVFdvu5RzJ3VU6huYedBeznYNAUBZu8bhmvp3v64B6dUE2nuTdyau7BhGpRVkhRQAK8ROBa6rKfemAzzk/XcWG6HvmePD53wF+roZu2DBnlaHrpgc0Yrar4L+9PxTJ3fhW02DRQFcgyUZp7sAUCk2W8Wo98zB2wv+vFpt7THSGBZMF9B4Ar3L+nnNdcEEIeA7CLUvqXBe5bLBRJcvuIAOJleNDnHpzROaAqMcw9RnNX7cRRu6MVMrvP3ZNl/Mcl6nXi9nfJyNxHqypkiWRqQRApy1RU1FP0dG+0jczVqYAXzIu3Qop7y8w37AfhWg5z+NQDmwEglr1nTqiKgnvMStX+DBk//Mg2fPvEDczUtZAUJGrlsNTWIVr8DJRkEBLtc2cJVbvexfKkyZyaO2ATu6W20fPMPQlVEp0tVxMghEgA/jWAn+y4IUK+COCLALBlyxZMTk4m2skglpeXMT/Xwnyb4sCBdwEAH54+hcn5M773LWn2bp768CO82jyPpm7i1rUrmJy8CQBoLbewpFHhfhy7aLPO9989gMHAsvH2jTbqLQOz8zqkNhH+/fJCCzNN8baDOHHB/qz3Drzlspj5WXsBZOoaJicnsby8jMnJSVxatG+2948eA7lhf33nLmiQCPC9732v42dFYVABjp+5hMnyjVR/d9rZ9wNvvYkKx8BuTdmvf/u738NQqfMNt9BoYe72DUxOenUH7JiTYKZp39wXLl8FAJw4/gHIjWI8yooEnL1wCZOT193Xzs7b38Ols6cwuXAm6k9TI80xA8COIYL/9PZp3G1cEv7+g0v293Dw3QMYSfA9MHx02w6qb79zELc32OfxwuU2QM3Y/bsTJlq6he99eAvbhyTfe89ds7f5/bcOYNuQHUhnl5q4syy+TyoycPrcRd95P3zD3sbRw4cwc1bC1GUNFgVee/379j6eP4dJ63Li4+Rx8bJ9rr71qr2t21cvYXLyWqZtdULa7zkLkgT3KQC7uH/vBMAf8TCAfQAmneXaVgDfIIR8jlJ6kN8QpfTLAL4MAPv376e1Wi3TTk9OTmLr5iG0Zxp47IlPAG++gUf27UNt31bf+xZbOvDqd3DnXXfjySd3AS9/Bw/ddw9qn7wLAPC1q4fw0c1l1Govhj7j+KtngNMf4QdfejEkvRxonsbrVy+gVKli+5YR1GqPh/7+z669j4Xri0hyjCfoWeDDD/HpmvdZL88ew9vXrmBkcAC1Wg2Tk5Oo1Wo4c3MJeOt13PfAXtQe3Q4AeLtxCsrli4k+KwrbDr+O8sgAarV0uXC275+q+c/TzKEpfPX0UTzyxNPuvMm/PHYNVVXGpx/cEtqO9so3cd9dd6BWe8B9jR1zEtxabAHf+y7GJjYDV6/hicc+gWfvHk91LFGovPYytmzfgVrtIfc1evoWcOA9vPD0E3h894ZCPgdId8wA8MPNU/i971/AE888H+qJDgBnXj8PnDqFT734QshLHofK+Rng0AE8+PCjeP6eCQDAy7MfoDp7M3b/XqQU/+HsJC7ONLBxbAS12vPu7xofXAeOvY9PPLEfD24bAaUUzZe/idFqSbjN0be+iw2bJlCrPeq+Nnd4CjhyFM8/+zTunBjEKZwDzp7G408+Dbz6Gh68/17Unt2T+Dh53D54BTh5DHc88Ajw5jvY/8iDqD2+M9O2OiHt95wFSdZq7wG4lxByJyGkBODzAL7BfkkpXaCUTlBK91BK9wA4ACAU2IuGItmeWTMmkcJ87rpJPZmFt0KqSmT7gYZmW7lEmnrJ8fO2Y33ucqoBxoT4ZRXmnAluX+hzN2nugdBZWxC0DbHmPixo+/uvXvkIvzV5LrQNzbCgmzSfLOOcl6J97oC4zfJ805Fl1njp/ukHtkA3Kb5/Zlr4+6yyTDVSc48/r4QQ/NhjdkCsBDX3wLVb10xYFMKEKsCGZHeyQgaL1/Jr7reW7FVzr8syHc8EpdQA8DMAXgZwCsDXKKUnCCG/Qgj53ErvYBTchKqTLBWO2eN87ky7GwxYIesxPveoYMNulHrbiPG5p7FC2sknPlHFnDMhK6SwcZiVu3nVxqFswZ0Nxggm2YJtfy2LYmquKfTS5x2xB6xchSog7ma40GAtYdd2gPLju8cwWlXx3Qjdvc06l6Y8H8xIwOekdNMKJfhF+LHH7JRclObOziW7NkRWSMB2zCxFau7++6OpRbdGSApGqG4t2ddorwf3RHcTpfSbAL4ZeO2XI95by79bnSE7Vsg45s5e0y0qTJDG+dyj2v0C/gHWccw9cUJVN0Pl4RXFSxjxEFeo0txMNWtnSD2ikIt1+WPM/fZyG5ph4faSKLjnG44NhH3uRSVUAbtoJxjc51lPlEr2B1IRUGQJn35wM14+fgP/7G/vDUkzbHxj2p497D7hV7aGKR6KE8Tu8QH88CPbsGd80Pd6KLg710YUcx+qhEfttQPMnQXzIhrGMUJ1e50E956tUFUlyZ10D4iZGiHE8cNzzJ3THaulcIk1QyxzdxiJYdHI4J6Fufs/owNz533uORsmAbYss9DUhcU6cYhic2xsGitkujLbAGAvxYM3bCHMnVWoasUWMQGsbN5/jcw3dAxXlDVp9xvETz63B0ttA187OBX6XUs3Mw0TYStc3oqomVbih+a//XuP43/7r+73vcb+lvWXYV1PRRWqbB/CRUzhrpCAF9xzTWKSmSzTD+5rCjZmz3QLeMSHojhWKRFzZxewyOveFIzYYyhznxXH3PmVRRzahhXyIVciNHdRhaph5h8rx7zuc4107F2LYHPBgR1X5hru74LSDNNV8zB3V3s1im0/AAAlJdwErpuKXB7ZOYYn92zAV968ELreRH7zJGAkiL83kmjucWD7oQdkmYEYWSa6t4zk+7+Xa8n+vbOH4K1FW3P/OPjcuxKqM6zD1dwjntiqw7pEwyCqgqUnQzxz54J7VBOlwNixOLQNM3QDukVMoQpVgc89YoZsGngaefKWAWw/ROdgqKSAEO8GvjzTdH8XCu4FMHdCiD1XdCUSqjIJtfydb2hdNYLtp37gLkzNNfGdE34ra1tQKZoEJUWCKhPUg5p7EUVCQeYemVAVMHfDHsghOfd7kbkW5p2/vdxGRe3tdr9ADwd3WbLLjuM0d4D1e7bQaIs1dyA87QUAGropbPcLhNuYiuDOUU0yLUcPT6ePKmJSZAkSCfdzz1uRydwtUUOJo8ASqkFIEsFw2Wv7yzP3oO4u+m6yQJZI4ZOYAMctI9Dcx6prm0zl8YN7t2D3xgH87vcv+F4XSX5JMVBS0OCuB93IOQwjsOp0NfcoWUbA3IMPmKAsk+eh7mrui+2uWZXlQc8Gd9WRZQwrWnMHnEHaPHMPuGUACB0zTc3AQMSTW9TgK/QeZiVLxNytcEI1grmz1/yNw/LNjgS88xJkSpRSfPOD65HyUhyb41sQXJlt4A7H7x4M7kUwd8Bezbm9ZYp0ywgGOy+s4aAOEWSJ4B8+vwcHL83hyBVvRoHo2koKWxbhe8vkY+5qlFsm4jQOVxToJvWtfoMtP4KtnnNZIZ1jWw/VqUAPB3fZCdoecxcfCpNlhD53J5iklWVKSZi7mpy5t3SRLOPXFH2fL/uDjWHFl4UnwZDD3JcCAzYOX5nHP/7q+3jrnNhHbTdPiwjuXPOwqbkmPrFrDBIRMPcC3DKAzdZdzb1It4xg9udaDuqIwn+zfxeGK4qPvYskv6QI9l6KkuCSIuhzX2oZKCtS5IOYNfmrBx4w/uAeYO4FuGWA3k+mAj0c3BVnvBa7UCKZu8Pw623DLkryzfqMkWXiEqoRU5L872H9sBPIMoKlcxxzD44rM8x8fawBvn+2P7izHipRHnjNpJHeZ9b2VzctXF9o4o7xQWwcLOP2sji452buMgGbA1G0W4Y/35RSW5bpIuYO2N/h33p4G944c9t9TST5JcVAWVkRzZ3dE9cXWpgYKke+XzRHtR2w3nrdQAtwy3ArnH5wX0OwYBZVIcm/z3CY+2DZP6NTVKjBEOwgyYO/CDox96RzLoNLZxbsRduvqLKvFatu5i9iimqxyph8VIdH3bB87iEejLlfm2/CosCuDVVsGi4LNPfo9sppwN/YaoFumdGq6nu4LbcNmBbtygBwx/gg5hu6GxDzyTKyL7AaMQ/yJCgHEqrHry5g7/aRmM8X2DEDRCgoy+QdkM3Q604ZoJeDu+wP7nFuGc3xuQ8Gggdjik3dH9Asi6KlW24JdhA+t0yMFZLfvzi0jTC7imPuQwEXgVFAEVNUi1U3uEfMQ7V97uLPZpr7ZcfjvmvjACaGSgLN3XTcGfkuR16aK7JCdffGAdxaarsBZJ5Vp3ZRQpVh54YqAODqvO1OEkl+STEQ8JlrEcnzpODbJy+1dJyfrmPf9tHI94uuybDm7pdl8g7IZujG7zYteje4M+be4Uvlfe4DASYe5ZZhF0qn9gNA/DxJICFzF3iRGfMXBc6hit9FYJhWrkQSYO+vKpNQcGf/jmTucQnViorFloErs3ag2bVxQMzctfCDNwv4wFOkFZI1PmMPqQXnXHRTQpVhhxPcpxx3Uh63zGCggjuv5i5LxKkst3Dy2iIA4OGd0cxdGNwDmrtbvFaALKNIBGxh342rsrTo2eDOglkn5s76vtcFAcSVZQLNieJ6uQNJE6ppmHvYi+w2Dotg7ryLoYjGYYQQoa94yUmIRk1ViipiAmzNfblt4NJMHapMsHWkgk3DZUwva74hycut6FYPacCkKVkK97rJgzucMvpLM/ZQDBbcuy2hCnjMfWrOfqBm9bkDYZ+5nrD9QBxY/uK4E9z37Yhm7syeWw8yd18RYXF9/Akh7oNwNKrhTQ+hZ4N7sBtcVEKRTVxvtM1QAGFWxxBz19gUpuyaeyrmnqL9AOAwdy7Ymlb+ClVAXBG47Gru0bJMFJtj/WVOXl/EjrEqZIlg01AZmmn5tndptuEyzjxg10BRU5gY7tjoZ+7zXdI0TISJwTJKioSrbnDPwdzLis8mrBtW7uuMmQGOX13A5uEyNg9XYj8fEAR3kSyj5WfugEemunFVlhY9G9zlQEJV1BUSYLKMw9wDVjtFllBSJDQCmjv7dxJZJurGScfc0/nchwNBWC+gKyTgBPeAts668kUx96giJsBjXievLWKXEyA3DdvuiNvLdok3pRRnby3jns1DufefBZ4im4YBwNiAiuGKgkszTnBn7X67MABIEsGOsarH3HXr/2/vXGPcuK47/rvk8LFc7kPSSqvVw5IsP2JZUuBEsZ02rteN29qxYSdoWthokARwYyRFAhTphxhwEQROviR9pAhqtDWQoA+gzetDqgZ2UiTx2okT+VG/5ciyLMmWLFlvrfa95PL2w8wdDodDckhekjO79wcY3tXOzt7LO3PmzP+ce07TzbEVubRd/E6lGy+2KctAOQb26juT7KrjtYO9yxmoyrWvkGWqNPf2jLv6rIws00NUNoT7OlZTc0+4VSGDXv1z6WRVnvus67mH0dzrH9Oo/ICqSe9/SAxmU/z1Hddw5+6xqt/xG+GiBllGnde/oatRtkzdPHfnBjk3s8imVZXGXRVnOjezyORcgSvWajDuzjWgMw0S7Nf1LWtyvOXz3KNqADat6uP4xTmklG3luftrL7WbCgn2fTE5V+DNM9N1JRko73vwXut+WcbNlim0X/IXPJ57RNe2GWJr3JXn3ii/NZUQbj33oE0yuVR12V93O3wNj0eVAIDG2TKNyv4qzz4oF/nPb7rc9Xi95LN2/rHyqIoaUiHB2e49X0OWqZstU1+WAdi82pZd1inP3THuh05PA7Bdg+eubnSdRcMUW1b387ZHc89Y0a09snG4j3cuzFIsEbB/oAAAGoNJREFUSUqy+UYdirIsYl9rJdn+W1HaSvDSsUlKsr7eDvZ9lrESFQ7Hou96c528xfazZaB8Hxrj3kPKBYPqN8ZVskwtz70v0HOvLjLmp1anJPfnIQuHqWyfZnKR3Q1HyqPSkAoJ1Vk40Dhbxu9JeRn0BKU2K889b2usfuOuRZZJqDiFXs8d7IyZ4xfmKC6VIlc0zM+mVX2cnV50A7+t5rkrZ2hmsehuFqyV9hqWdDLhpmk2kmXAlvaq8ty9nrvlk2XaXHv1WQ2ZVMjeYSXKxlMI3CpxVcepPPca6Xa5dLUUoS6UWrIMlI1344BqSM+9Ce/KLfLleNM66rmDrXHWNO7zhYoMF0VhqXZN+0rP3Tbug30W6WTC3aV66PQ0uXSSDUO1A2thUTe2blkG7KBqsSQ5OTnPZMSKhvlRwenDZ+w3jZZ3qCpZZmHJNe5ta+7Ow2Ekn2F0sPbuVIU/Y6dmbRlNmnvaMp57z/F67vUWNJUQTM0XkJKqPHewDXiVLNMgFRI8O0hrXOwqraqh515HlqlFPmNfeMrw6qjnDupGqhyvSoUsLMnAB1W9gKp3l99ljnEXQlTkur95Zprta/NaUhfL2TL6L2uV6/7WuVkuzkaraJgfFd9484z9VtS6LONo3gtFt1mJjlRIgJ0bB0Otub9hR1VtGZ8s0262TMZK0JdK1nRY4kRsZ1AuP7BUd0GtZMJ9PQ3y3PvrBFRzqdZlGfuYRMPCYcr4Z5uRZXxFvgql9gNd6rzTC0VKngqQU/PFwGbXYO/kLdapJT+QsWu696eTrPIYwxGvcdeUKQPlzAndqZDgyXU/P+N47tE17huHbc/9TUfyajnP3RNQdWUZDZo7hJNkwOmjWiegmnA2Rs1qaq+YsRLLwmuHOBv3ZFn2qOepqaqQEFyYKpe2qjoxzTnf15Nl1EVazyvKppINPXflKWeb2KHpr7mho3CYfV4n79+5URaLJRaKJddY+HX3Qqn+DZ9ICPIZi82rcxVe2tp8mrPTi8wsFDkxOc/2tf2Bv98sbkC1A63v1g9mSScTvK089wgbgNHBLFZCcPisI8u06bnPLC65hdPaz3O3z9komOodQ0VA1SfLgP0wX2pQ+jss+YzFyEB0JbdmiO02LMuTLVPvgvNKBkHZMsEB1SW7gmQDrxzqa5CZVGPPXckezTRa9mruUtres54895R7Xu+Gpg3DfRx4d6rKc1cPzXqfwVBfqirjZ+1AhhePTbqygS7PPdnBgGoyIdi0us+WZeaiHVBNJgRjw1mPLNP6DlWwNxHp0txVm76wxj2fTXHU2V+g3hSDWk8qebNdJ+eB299TUZQvzsTeuC8U62vuXq8+KPsll066nqqiXrlfRcZKVLT7Cj4m2bBZh3rl9Hetr0fZcy+4zUp05Ll7NVYoB2zLnntwP8t6xvSrH93ppj8q1uYznJ9Z4PV3pwB9xj3lau76jTvYQdWDp6eYL5QiuTvVy6bhHE8fOQe07rnn0l7jrkdzz6SSrO5Phw6g5zNJ93pU1ST9xj1lJWBBT9kJJb8tB+Jr3FVVyEJ9zd1reGqlQvpry8zVadShyFiNgy7ZUJ67feEONmPcPZp70bnpau3QbQZ/q72pBdtT36CMe5XnrtLjan8Ot1y9rurf1g5kKEl45sh5rITQdkNZHZRlwL7xJw7atdKjLMuAnTFTOmx/3Wq2jLffQVlzb+86+9zN2/mT928KbYS9AVXlnfvfHjpVdiLuxNe4ewqH1QsYWQ1kmVzKYnGpVLERyE6brP/RpK1EQ+MexnNXBnOgCVmmP102wqpBuI765f5We+rBs2HY9rL8mru/E31Y1C7VfUfOsWVNTlu5ALV+nZBlwM74UdmgUZZloFxADFqXZdxNRAvFUA/yMISVYxT9GYtZZ8OeGoP/TSTVwUB6nIltQNW7Q7VutoxXlgkw2P2+ICLYnnsYWaaRUQvnuRdIJkRTjSrU8dMez11L4TBfFk6VLOPbpVqo8ZrcCGXcj52fY7uGsgOKsizTKc+9HDuIcp47lNcMWpdloFw8LEx8pRN4N+yVZUC/cbfXXWcN/+VAbI27WuBGmnulLBMcUIXKPqr1+qcqMiFyYTNWsmHhsCkneNmsVqgCnipjRVfhMCh77kqeWZPPkLES1dkyLeqwapcq6NPbobMBVag07lGXZVSuO7TuuYMTk1pY0pYK2Sx5T/KA+6ZYw3Pv9tiiTmw/DfWULjYod+s1erUCqlBZ9ne2sFSz3K/iz264jL+89aq6x2SsRMOSv9488mbIZy2mFsqeu67CYVAua6AyefIZy+6qVEtzb/Km8qaa6TTunawtA7bBVM/gWMkyLWru4Gjei0U3mNmpB2ct1JvdD//veO2AqqeOv6FMbDV370VWrwuRWviECH497UtVVr4DO899bLB+NP/Gy9c0HKOd595YlmkmmKoYcIp8lWUZPYXD7DGpgKrK5LEYzFrV2TIt3vC5tOW+eeg07uohryO4HEQ2lWT9YJaTk/OR3qEKsH4oS0JASTa3Qc5PfybJzMIShRqSSKe5fttq7tw9xj/+4pC7y9kvDanrz3julcT20/A+pcPIMv3pYOkjyHOfmq/dHLsZwnjul+Za99y9sowOj0q12pvxpEKmknYZhUDPvcWAKpR1d52au1s4rIMe3GWrcyQTggEN10cnSSUTrHcclLY8d5/m3gsD+pW7riWXSfLQj18DjOceltgad+9FFiagmgvIlIFq414qSc5MLbAuRFGjRoTx3C/NF5rKcVfk/Z67BilCtdqb9mjuKh4wmE1VZ8u0kUGxNp9hbCir5SGqcFPiOmiArhzNs24go7WNX6dQuns7QdBqzb378x7JZ/jynTs4P2M3SanaoerKcdFfk24SbfejDmE9d8vjuQehct9VyYELs4sUS5LRgfaNe5jCYVPzxaZ2pyrymZRT0EnPtvDyecvGfWq+6Aa0BvtSbps5RTtBtntv2MzkbHAZ4VbpdCokwF/9wdV8+ne2dez8Otm4qo/0sUTdjXaNUA/7XgVUFR+7biM/evEETx48UzsVsgcPnigTW+PuzesOs4kprOd+6pJd0Gq0geYeBluWKSGlrOnpTc0XWpJlBrIWU/OeHao6jft82bgPOCUJbM3dn+feenrcx67b1OZIq+l0QBVgVX+aVf3RToNU3HrNqFtzpVX6ndpLbipkj6olCiH4+h/v4uHHD3HN2GDFz9KuLBNbIaIjhPo0hBC3CSFeF0IcEkI8EPDzLwohXhNCvCyE+LkQYov+oVbiDZrV8yZcWaam515p3E9P2b09dcgyqh+jki/8SCmZXihWlMYNS97nUekyaN5We9MLhQrP3V/TvZznHg2PqSzLRGM8veaO3WN8697r2jpHLpNkZrF3qZBexob6+NpHd1Xdy+XeuWbdvTRcKSFEEngYuB3YAdwrhNjhO+wFYI+UcjfwQ+AbugfqxyvFhPHcg8r9QnWe+2nHc6/XlT0sjRp2zCwuUZLN7U5V5LMWJVlOV9Rl0PqrPHfHuGdTVTXdo3DDe0mafGft5NMWi8WS6/xE0YCagGowYe6C64FDUsrDUspF4LvA3d4DpJSPSymVILsP0P/O7cMKq7m7AdX6mrvyVk9d0ue5r3Ze30875/SjZI5WA6oAF2bsc+gyaN5We9MLZc1dbdrxZsxEzbh3unDYSkTdNxfn7GBmVNbaiyk/EEyYldoIHPN8f9z5t1rcBzzWzqDCkAzpuSuPNl9Dlkkm7FQ/13OfWmA4l2prV5/i2g12HY1XT0wG/rxcEbI1zR3sADDo81q8rfamPRusVD9Ur+6+2MP0uCDcZh0RGc9yQL3xquB3VNbaSzdiLXEkjFUJshqBURohxCeAPcDNNX5+P3A/wOjoKBMTE+FG6WN6eponnniCpIAlCefPna15rtfO2Ub7/JmTTEycDzwmJUq8cfRtJiZOsf/wPPlEqeWxeVkqSdIJeGzfflZNHqr6+RsX7LEdef01Js4frHuu6enpijEdOW0b4JcO2Od9+YXnuXS4/QfShTMLTM4UmZiYYHJ2kfOnTjIxcY6jZ+2/N/HrZ3hnlf13fnvUvuGf2fdr+lP6vSb/nBvxxgl7jMffPsrExAnt4+kGzc6507x10v5M33j7BAL45ZNPaP8b7c75zClbSr00eSFSn109urHOYYz7cWCz5/tNQNWdI4S4FXgQuFlKuRB0IinlI8AjAHv27JHj4+PNjheAiYkJxsfHsX72GEvFEmPrRxkfDw4c5Y6ch2d/w9WXb2V8/OrAY4b2/YJVI2sYH38v39z/FNuGLMbHb2hpbH52HniKiyLB+PgHq34mD5yGp5/lQze8n+suW1X3PGrOir7D5/iH5/cxtHYM3nybG67/QFUWQSs8XzjI/771Bjf+7k0Uf/ITrr3qcsbHr2D42EX+9rmnuOKaXYy/xy7je+CJN+HAAW65+aaaAet28M+5ETMvn4SXn+eK7faY40izc+40pQOn+KeXniPVP0TautiRsbU754lL++HYUdaNrGF8/Hp9A+sg3VjnMO8xzwJXCiG2CSHSwD3AXu8BQojrgH8B7pJSntY/zGDCaG1Wg1RIcLoxFWwP5cyleS3BVMWujUPsPzFZ0ZdUUS7324Lm7soy6nVZVyqk/TmpwLIrywT0Ue3VlvRaKGlKR/ljg416aF+cLXS9ImRYylUhozm+XtHw05BSFoHPAz8Ffgt8X0q5XwjxkBDiLuewvwHywA+EEC8KIfbWOJ1WkiECaOpGr1efPZdOMru4RKkkOT21wKiGYKpi58YhZhaX3H6WXi65jTpa0Nyd/POLjuauLxXSPu/JyTnn+3IqJFRq7oWlEkJEJ5BV7qEajfEsB9R9MzlXaLuWe6foxua1OBLKqkgpHwUe9f3blz1f36p5XKEIczO7nnudEr59KXuLtbs7VcMGJsWuTU5Q9Z3JqiJZUzo89xndqZD25/Suk+GjjPuA67l7mhUvSVLJRGS24puAqn7U9XBhdjGyZY5NKmQwsb4L1GLWW9SxoSybVvXV1aP7MxazhaK7O9Xf87MdrlibJ5tK8Mo71RkzU/NFrIQg20JhJ3XTKc9dlzSijPi7k45xd77PWEmyqUSV5x6lV/WUK8uYm1wXqvbPfKEUGfnNT9rUlgkktuUHoCxF1JMkhnNpfvWl3697nj5Hljnl7k7V57lbyQTXjA3WMO4FBvtSLXm+qoer0tx1XdjqNfykY9y95YgHs6mqPPcovQonu1A4bKXhfeON0oPci3ljCybWn4Zbv7tNw5ZLJZlbXOJMBzx3sIOqr524VBVUbbVRh2IgYzHnlBTWdWHn/Z67Z/PXYF+qoqa7bdyjcwkZ7VU/3iyoqMYyzCamYKJzZ7aArq7nKqCqc3eql50bh5heKHLkXGVQtV3jnvf8rs7CYQAnL1XKMuAUD/N47otFGSnjbjaz6CeZEPQ5NZKitNZeTCA9mGiuVkhcWabNRe1LW8w5sswqTbtTvexyOr6/crxSmrk0V3CzXlrB61XrLBwGcMrx3L0PH9tz9+5QLfWsSmAQo4NZ0laCzav7Gh9sCI2K70TXuDeWZ1cisf40LE35rbl0ksWlEicu6s1xV1y5Lk/Gqg6qtu25Z/R77iqAdnpqnnQyUfGgszV3jyxTjJbmPjqY5bcP3cbuTcO9HsqyQl0TUdXcTbZMMNFcrZDolGUAjp6b0S7JQO2gqgqotop6MCQTQls6omq1V5KVkgzY9WWqsmUi5LmDucE7gdLdUxEp7ezHyDLBROvObBJL0xNbXbzHzs9qzXH3EhRU1eW56zRoqtWe9/wKlS2jarovRiygaugMqnhYVNfaBFSDieZqhSTMDtUwKM+9sCS1Z8oodjlB1becVnWlkmR6sdjSBiaF8qx153X7Ny4pBvvsmu4qQydq2TKGzqAe9lFd6/IbfDTH1yti/WmkNKVC9nlyeTvluW9f1w/AkbPTAEwtFJGytdIDClUqQHd+b76O5w646ZCFJRlZHdagDxVQjepaq7IIxnOvJJqrFRIVSG3Xo8hVGPfOeO5b1yjjbnvu5dIDbeS5K89ds9ZY23OvLB4WtU1Mhs6gZMuoatpuD9WIjq9XxNq4p0KUHwiD17iv7UC2DNhdmQayFkedAmJTbtGw9lMhdb+O9rvGvXJsZc/dNu6LRSPLrASirrlbbtmJaI6vV8T609CnuZc91E557kIIto30c/RcpXFvS3PPdMajUlp+lSzja7W3uFSKbKVAgz6irrmra9BkSlUSzdUKia781krPvTPGHWxp5ojrubcvy7gBVd2au/Ow86dCqs9GSUtRKxxm6AzlPPdoGs+UK89Gc3y9ItZ3ZrlQlJ6Aaid2p3rZOtLPiYtzLBSX2uqfqhhwZRm9F3V/Dc1943Af71k/wGOvnASgUDQB1ZVALuKyjMq/N806Kon1p6Fvh6ptxDqVKaPYNpKjJO18+na6MCmUZ609W8Y570Cm+sFz5+4xnnvrAicuztkB1YhubDHow5VlIirBuXnuxnOvIJqrFRJdO1RVYSSdpX6D8GbM6PDc85lOZcvYn4dflgG4Y/cGAB595aTZxLRCUGWgo7rWI/0ZBrIWW1bnej2USBHveu6adqYlE4KMlejYBibFthHbuB89O8Ol+QJpK0E21boM5Hru2jcxpSr+72XbSD/Xbhjkxy+fNJr7CiHn5rlH0zMeyqV45St/1OthRI5Y35mWJs0d4JMf3MIdu8faPk89hnNphnMpjpybYWq+2NYGJij3UdUty6hNK7XeKu7cvYEXj12MdHcegz7KWVlmreNErFdL5XfrCKQ8eMcObrl6XdvnacTWNf0cPTvj1JVprydlNpUgmRDaZZnta/OkrQSX1XjNvdPzEDTGffkT9YCqIZhYr5YVw96J20aUcS+0pbeDnTufz1jaswR2bhzi4NduZ8NwcF30zatzvHezXVbXBFSXP0pzj6osYwgm1sY9TIPsqLF1TT8nJuc5M7XQ1u5URT5j9aQh9J27bO/daO7Ln/VDWXZtHGLHhqFeD8XQBLG+M1OasmW6ydYRW+o4eGqqbc8dYMuaHOuHOpvlE8Qdu8dIWwlG8p0NQht6TzaV5H++8CHev2VVr4diaIJYZ8sk3TZ78XlGqYyZwpLUYty//akP0Iu9GxuG+/jVl25hTb8x7gZDFIm1cY+j5r7VMe7Q3gYmhbdccbfpREtCg8Ggh/i4vAFYMdTcB7Mp1vSngfY2MBkMBkM94m3cY9peS3nvOgKqBoPBEES8jXsMPXcolyEwnrvBYOgU8TburuYer2lsczJmdGjuBoPBEES8rKKPtfkM6WTCbf8WF8qyTLzGbTAY4kOsjfut14zyqwduYTiX7vVQmuLmq9bymZu28T6TN2wwGDpErF3HRELEMh1vIJviwTt29HoYBoNhGRPKcxdC3CaEeF0IcUgI8UDAzzNCiO85P39aCLFV90ANBoPBEJ6Gxl0IkQQeBm4HdgD3CiH8bud9wAUp5RXAN4Gv6x6owWAwGMITxnO/HjgkpTwspVwEvgvc7TvmbuDfnK9/CHxYCBGv/ESDwWBYRoQx7huBY57vjzv/FniMlLIITAJrdAzQYDAYDM0TJqAa5IHLFo5BCHE/cD/A6OgoExMTIf58NdPT0y3/blwxc14ZmDmvDLox5zDG/Tiw2fP9JuBEjWOOCyEsYAg47z+RlPIR4BGAPXv2yPHx8RaGDBMTE7T6u3HFzHllYOa8MujGnMPIMs8CVwohtgkh0sA9wF7fMXuBTzlffxz4hZSyynM3GAwGQ3do6LlLKYtCiM8DPwWSwHeklPuFEA8Bz0kp9wLfBv5DCHEI22O/p5ODNhgMBkN9RK8cbCHEGeCtFn99BDircThxwMx5ZWDmvDJoZ85bpJRrGx3UM+PeDkKI56SUe3o9jm5i5rwyMHNeGXRjzrGuLWMwGAyGYIxxNxgMhmVIXI37I70eQA8wc14ZmDmvDDo+51hq7gaDwWCoT1w9d4PBYDDUIdLGfSWWGg4x5y8KIV4TQrwshPi5EGJLL8apk0Zz9hz3cSGEFELEPrMizJyFEH/qrPV+IcR/dnuMuglxbV8mhHhcCPGCc31/pBfj1IUQ4jtCiNNCiFdr/FwIIb7lfB4vCyHep3UAUspI/oe9YepN4HIgDbwE7PAd8xfAPztf3wN8r9fj7sKcbwFyztefWwlzdo4bAJ4E9gF7ej3uLqzzlcALwCrn+3W9HncX5vwI8Dnn6x3A0V6Pu805/x7wPuDVGj//CPAYdm2uG4Gndf79KHvuK7HUcMM5Sykfl1LOOt/uw671E2fCrDPAV4FvAPPdHFyHCDPnzwAPSykvAEgpT3d5jLoJM2cJDDpfD1FdwypWSCmfJKDGloe7gX+XNvuAYSHEmK6/H2XjvhJLDYeZs5f7sJ/8cabhnIUQ1wGbpZQ/7ubAOkiYdb4KuEoI8ZQQYp8Q4rauja4zhJnzV4BPCCGOA48CX+jO0HpGs/d7U0S5h6q2UsMxIvR8hBCfAPYAN3d0RJ2n7pyFEAns7l6f7taAukCYdbawpZlx7LezXwohdkopL3Z4bJ0izJzvBf5VSvl3QogPYter2imlLHV+eD2ho/Yryp57M6WGqVdqOEaEmTNCiFuBB4G7pJQLXRpbp2g05wFgJzAhhDiKrU3ujXlQNey1/d9SyoKU8gjwOraxjyth5nwf8H0AKeVvgCx2DZblSqj7vVWibNxXYqnhhnN2JIp/wTbscddhocGcpZSTUsoRKeVWKeVW7DjDXVLK53ozXC2EubZ/hB08Rwgxgi3THO7qKPUSZs5vAx8GEEJcg23cz3R1lN1lL/BJJ2vmRmBSSnlS29l7HVFuEG3+CHAQO8r+oPNvD2Hf3GAv/g+AQ8AzwOW9HnMX5vwz4BTwovPf3l6PudNz9h07QcyzZUKuswD+HngNeAW4p9dj7sKcdwBPYWfSvAj8Ya/H3OZ8/ws4CRSwvfT7gM8Cn/Ws8cPO5/GK7uva7FA1GAyGZUiUZRmDwWAwtIgx7gaDwbAMMcbdYDAYliHGuBsMBsMyxBh3g8FgWIYY424wGAzLEGPcDQaDYRlijLvBYDAsQ/4f870cMC5nxj4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def d(func,rangesize,*args):\n",
    "    y=np.array([func(*args) for i in range(rangesize)])\n",
    "    x=np.linspace(0,1,rangesize)\n",
    "    plt.plot(x, y)\n",
    "    plt.grid()  # 生成网格\n",
    "    plt.show()\n",
    "d(random.uniform,100,0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.1951769703244186,\n",
       " 0.8119677753430801,\n",
       " 0.33207092131217053,\n",
       " 0.5074727229555104,\n",
       " 0.8875155275422096,\n",
       " 0.37844871014896675,\n",
       " 0.7360115448928031,\n",
       " 0.7891326360218672,\n",
       " 0.31661832127417733,\n",
       " 0.016525871376144474]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 随机数\n",
    "[random.uniform(0,1) for i in range(10)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 规律分布随机数\n",
    "mu=1;sigma=1\n",
    "random.gauss(mu,sigma)    # 随机生成符合高斯分布的随机数，mu,sigma为高斯分布的两个参数。\n",
    "\n",
    "lambd=1\n",
    "random.expovariate(lambd) # 随机生成符合指数分布的随机数，lambd为指数分布的参数。\n",
    "y=np.array([random.expovariate(lambd)  for i in range(100)])\n",
    "x=np.linspace(0,1,100)\n",
    "plt.plot(x, y)\n",
    "plt.grid()  # 生成网格\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\program files\\python36\\lib\\site-packages\\matplotlib\\axes\\_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([0.00129188, 0.00516752, 0.00516752, 0.00516752, 0.00775127,\n",
       "        0.01291879, 0.0180863 , 0.03488073, 0.03746449, 0.05038327,\n",
       "        0.05684267, 0.08138836, 0.08009649, 0.11368533, 0.08655588,\n",
       "        0.11110158, 0.09043152, 0.10722594, 0.07234521, 0.06976146,\n",
       "        0.06459394, 0.04650764, 0.03617261, 0.02842133, 0.02067006,\n",
       "        0.01679442, 0.01162691, 0.01033503, 0.00516752, 0.00387564]),\n",
       " array([72.81542778, 73.5894942 , 74.36356063, 75.13762705, 75.91169347,\n",
       "        76.68575989, 77.45982632, 78.23389274, 79.00795916, 79.78202558,\n",
       "        80.55609201, 81.33015843, 82.10422485, 82.87829127, 83.6523577 ,\n",
       "        84.42642412, 85.20049054, 85.97455696, 86.74862339, 87.52268981,\n",
       "        88.29675623, 89.07082265, 89.84488908, 90.6189555 , 91.39302192,\n",
       "        92.16708834, 92.94115477, 93.71522119, 94.48928761, 95.26335403,\n",
       "        96.03742046]),\n",
       " <a list of 30 Patch objects>)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "from numpy.linalg import cholesky\n",
    "import matplotlib.pyplot as plt\n",
    "sampleNo = 1000;\n",
    "mu = 85\n",
    "sigma = 4\n",
    "np.random.seed(0)\n",
    "s = np.random.normal(mu, sigma, sampleNo )\n",
    "plt.hist(s, 30, normed=True)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
